{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 决策树"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['axes.labelsize'] = 14\n",
    "plt.rcParams['xtick.labelsize'] = 12\n",
    "plt.rcParams['ytick.labelsize'] = 12\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 树模型的可视化展示"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 下载安装包：https://graphviz.gitlab.io/_pages/Download/Download_windows.html  树模型展示时会用到.下载后如下网址配置环境变量。\n",
    "- 环境变量配置：https://jingyan.baidu.com/article/020278115032461bcc9ce598.html\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(max_depth=2)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris #导入鸢尾花数据集\n",
    "#见：https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html#sklearn.datasets.load_iris\n",
    "from sklearn.tree import DecisionTreeClassifier #代入决策树分类器\n",
    "#见：https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html#sklearn.tree.DecisionTreeClassifier\n",
    "\n",
    "iris = load_iris() #样本是4维的\n",
    "X = iris.data[:,2:] # 样本，但这里只取后两维的数据 即0 1 2 3中的2 3作为样本。\n",
    "y = iris.target#标签\n",
    "\n",
    "tree_clf = DecisionTreeClassifier(max_depth=2) #实例化，树的最大深度设为2\n",
    "#【补充】学生的可以自行操作下最大深度是4的情形。\n",
    "tree_clf.fit(X,y)#训练\n",
    "# print(iris)#可以看看数据长什么样。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['petal length (cm)', 'petal width (cm)']\n",
      "['setosa' 'versicolor' 'virginica']\n"
     ]
    }
   ],
   "source": [
    "#画图展示：借助上面安装Graphviz软件\n",
    "from sklearn.tree import export_graphviz #先在sklearn中用export_graphviz方法书写代码。\n",
    "#见：https://scikit-learn.org/stable/modules/generated/sklearn.tree.export_graphviz.html#sklearn.tree.export_graphviz\n",
    "\n",
    "export_graphviz(\n",
    "    tree_clf,\n",
    "    out_file=\"iris_tree.dot\",\n",
    "    feature_names=iris.feature_names[2:],\n",
    "    class_names=iris.target_names,\n",
    "    rounded=True,\n",
    "    filled=True\n",
    ")\n",
    "#tree_clf是上述训练好的模型，out_file是指定输出的.dot文件(下面可以把它转化成png,这里也可以指定生成后文件存放的路径)\n",
    "#feature_names是画图当中特征的名字，class_names是画图中用到的标签。\n",
    "# rounded，filled是绘图的一些功能显示。\n",
    "\n",
    "#执行完上述代码会生成iris_tree.dot文件\n",
    "\n",
    "print(iris.feature_names[2:])\n",
    "print(iris.target_names)\n",
    "#【补充】这里输出特征名字，后续我们修改下名字。\n",
    "#【补充】在print(iris.target_names)后得到的是['setosa' 'versicolor' 'virginica']\n",
    "#【补充】后续换类名时要写出“逗号”，即['label 1', 'label 2', 'label 3']，否则报错。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "然后，你可以使用graphviz包中的dot命令行工具将此**.dot**文件转换为各种格式，如PDF或PNG。下面这条命令行将.dot文件转换为.png图像文件：\n",
    "\n",
    "$ dot -Tpng iris_tree.dot -o iris_tree.png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "image/png": {
       "height": 400,
       "width": 400
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image #在notebook中展示图片的方法\n",
    "Image(filename='iris_tree.png',width=400,height=400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(max_depth=4)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris #导入鸢尾花数据集\n",
    "from sklearn.tree import DecisionTreeClassifier #代入决策树分类器\n",
    "\n",
    "iris_tmp = load_iris() #样本是4维的\n",
    "X_tmp = iris.data[:,2:] # 样本，但这里只取后两维的数据 即0 1 2 3中的2 3作为样本。\n",
    "y_tmp = iris.target#标签\n",
    "\n",
    "tree_clf_tmp = DecisionTreeClassifier(max_depth=4) #实例化，树的最大深度设为2\n",
    "#【补充】学生的可以自行操作下最大深度是2的情形。\n",
    "tree_clf_tmp.fit(X_tmp,y_tmp)#训练\n",
    "# print(iris)#可以看看数据长什么样。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import export_graphviz #先在sklearn中用export_graphviz方法书写代码。\n",
    "#见：https://scikit-learn.org/stable/modules/generated/sklearn.tree.export_graphviz.html#sklearn.tree.export_graphviz\n",
    "\n",
    "export_graphviz(\n",
    "    tree_clf_tmp,\n",
    "    out_file=\"iris_tree2.dot\",\n",
    "    feature_names=['feature 1', 'feature 2'],\n",
    "    class_names=['label 1', 'label 2', 'label 3'],\n",
    "    rounded=True,\n",
    "    filled=True\n",
    ")\n",
    "#【补充】由于上面我们已经print了特征和标签名字，这里就可以修改。\n",
    "#【目的】更清晰的知道决策树中哪里用到特征，哪里用到标签。\n",
    "\n",
    "#【实操】运行完上述内容，cmd下同文件夹下运行dot -Tpng iris_tree2.dot -o iris_tree2.png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 38,
     "metadata": {
      "image/png": {
       "height": 400,
       "width": 400
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image #在notebook中展示图片的方法\n",
    "Image(filename='iris_tree2.png',width=400,height=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 决策边界展示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "def plot_decision_boundary(clf, X, y, axes=[0, 7.5, 0, 3], iris=True, legend=False, plot_training=True):\n",
    "    x1s = np.linspace(axes[0], axes[1], 100) #构建网格数据的x1轴\n",
    "    x2s = np.linspace(axes[2], axes[3], 100) #构建网格数据的x2轴\n",
    "    x1, x2 = np.meshgrid(x1s, x2s)\n",
    "    X_new = np.c_[x1.ravel(), x2.ravel()] #和之前代码一样构建网格数据\n",
    "    y_pred = clf.predict(X_new).reshape(x1.shape) #计算预测值，并和样本网格一一对应，做预测。\n",
    "    custom_cmap = ListedColormap(['#fafab0','#9898ff','#a0faa0']) #颜色列表\n",
    "    plt.contourf(x1, x2, y_pred, alpha=0.3, cmap=custom_cmap)#绘制等高线并填充区域颜色\n",
    "    if not iris: #是否展示等高线的线条边界\n",
    "        custom_cmap2 = ListedColormap(['#7d7d58','#4c4c7f','#507d50'])\n",
    "        plt.contour(x1, x2, y_pred, cmap=custom_cmap2, alpha=0.8)#等高线的展示\n",
    "    if plot_training: #训练数据的展示，按照分类的颜色绘制训练样本数据。\n",
    "        plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"yo\", label=\"Iris-Setosa\")\n",
    "        plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"bs\", label=\"Iris-Versicolor\")\n",
    "        plt.plot(X[:, 0][y==2], X[:, 1][y==2], \"g^\", label=\"Iris-Virginica\")\n",
    "        plt.axis(axes)\n",
    "    if iris:\n",
    "        plt.xlabel(\"Petal length\", fontsize=14)\n",
    "        plt.ylabel(\"Petal width\", fontsize=14)\n",
    "    else:\n",
    "        plt.xlabel(r\"$x_1$\", fontsize=18)\n",
    "        plt.ylabel(r\"$x_2$\", fontsize=18, rotation=0)\n",
    "    if legend:\n",
    "        plt.legend(loc=\"lower right\", fontsize=14)\n",
    "\n",
    "plt.figure(figsize=(8, 4))\n",
    "plot_decision_boundary(tree_clf, X, y)\n",
    "#https://scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html#sphx-glr-auto-examples-tree-plot-unveil-tree-structure-py\n",
    "#在各个节点考虑特征是否是当前的最好特征时sklearn实际的切分，由于特征是连续值，所以类似于之前讲过的“二分”，这里的具体数值由上述网页可以做实验得到。比如tree_clf.tree_.threshold\n",
    "plt.plot([0, 7.5], [0.8, 0.8], \"k-\", linewidth=2) #见上述内容 #两点(0,0.8)和(7,0.8)连线，手动绘制depth=0时的分割线。\n",
    "plt.plot([0, 7.5], [1.75, 1.75], \"k--\", linewidth=2)#见上述内容#两点(0,1.75)和(7.5,1.75)连线，手动绘制depth=1时的分割线。\n",
    "plt.plot([4.95, 4.95], [0, 1.75], \"k:\", linewidth=2)#见上述内容 #如果有第三层，即depth=2时再这样类似绘制，这个例子中没用到。\n",
    "plt.plot([4.85, 4.85], [1.75, 3], \"k:\", linewidth=2)#见上述内容 #如果有第三层，即depth=2时再这样类似绘制，这个例子中没用到。\n",
    "plt.text(1.40, 1.0, \"Depth=0\", fontsize=15)#展示第1次特征的切分\n",
    "plt.text(3.2, 1.80, \"Depth=1\", fontsize=13)#展示第2次特征的切分\n",
    "plt.text(4.05, 0.5, \"(Depth=2)\", fontsize=11)#展示第3次特征的切分  #这个例子中没用到。\n",
    "plt.title('Decision Tree decision boundaries')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 概率估计"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**估计类概率**\n",
    "输入数据为：花瓣长5厘米，宽1.5厘米的花。 相应的叶节点是深度为2的左节点，因此决策树应输出以下概率：\n",
    "\n",
    "* Iris-Setosa 为 0％（0/54），\n",
    "* Iris-Versicolor 为 90.7％（49/54），\n",
    "* Iris-Virginica 为 9.3％（5/54）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.        , 0.90740741, 0.09259259]])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_clf.predict_proba([[5,1.5]]) #给定一个样本，由训练好的树模型可以得到该样本落入哪个叶子节点上，输出训练集叶子节点的样本的标签的分类概率\n",
    "#即 对应于上述ABC三个类别 0/54 49/54 5/54."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_clf.predict([[5,1.5]])# 由上述分类概率，最大的概率即为该分类。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 决策树中的正则化\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**DecisionTreeClassifier类**还有一些其他参数类似地限制了决策树的形状：\n",
    "\n",
    "* min_samples_split（节点在分割之前必须具有的最小样本数），\n",
    "\n",
    "* min_samples_leaf（叶子节点必须具有的最小样本数），\n",
    "\n",
    "* max_leaf_nodes（叶子节点的最大数量），\n",
    "\n",
    "* max_features（在每个节点处评估用于拆分的最大特征数）。\n",
    "\n",
    "* max_depth(树最大的深度)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'min_samples_leaf=4')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_moons #之前用过这个数据集合，“两个半圆”\n",
    "X,y = make_moons(n_samples=100,noise=0.25,random_state=53)\n",
    "tree_clf1 = DecisionTreeClassifier(random_state=42) #不做限制\n",
    "tree_clf2 = DecisionTreeClassifier(min_samples_leaf=4,random_state=42) #限制min_samples_leaf，与上述的不做限制的做对比。\n",
    "#因为这里就100个样本，所以这里设置min_samples_leaf=4。当样本量增加时，这个min_samples_leaf的取值可以适当的增加。\n",
    "tree_clf1.fit(X,y)\n",
    "tree_clf2.fit(X,y)\n",
    "\n",
    "plt.figure(figsize=(12,4))\n",
    "plt.subplot(121)\n",
    "plot_decision_boundary(tree_clf1,X,y,axes=[-1.5,2.5,-1,1.5],iris=False)#横纵轴的取值范围需要多次尝试确定。\n",
    "plt.title('No restrictions')\n",
    "\n",
    "plt.subplot(122)\n",
    "plot_decision_boundary(tree_clf2,X,y,axes=[-1.5,2.5,-1,1.5],iris=False)\n",
    "plt.title('min_samples_leaf=4')\n",
    "\n",
    "#可以看到不加限制的左侧图像在有些地方是过拟合的。如果有新样本做预测的话，按照这个判断就会产生错误。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对数据的敏感"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 792x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(6)\n",
    "Xs = np.random.rand(100, 2) - 0.5\n",
    "ys = (Xs[:, 0] > 0).astype(np.float32) * 2  #大于0的x设为标签2，小于0的x设为标签0\n",
    "\n",
    "angle = np.pi / 4 #指定旋转角度\n",
    "rotation_matrix = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]])#构造旋转矩阵\n",
    "Xsr = Xs.dot(rotation_matrix)#执行一次数据旋转\n",
    "\n",
    "tree_clf_s = DecisionTreeClassifier(random_state=42)\n",
    "tree_clf_s.fit(Xs, ys)#对未旋转的数据训练决策树\n",
    "tree_clf_sr = DecisionTreeClassifier(random_state=42)\n",
    "tree_clf_sr.fit(Xsr, ys)#对旋转的数据训练决策树\n",
    "\n",
    "plt.figure(figsize=(11, 4))\n",
    "plt.subplot(121)\n",
    "plot_decision_boundary(tree_clf_s, Xs, ys, axes=[-0.7, 0.7, -0.7, 0.7], iris=False)\n",
    "plt.title('Sensitivity to training set rotation')\n",
    "\n",
    "plt.subplot(122)\n",
    "plot_decision_boundary(tree_clf_sr, Xsr, ys, axes=[-0.7, 0.7, -0.7, 0.7], iris=False)\n",
    "plt.title('Sensitivity to training set rotation')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 回归任务"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "m=200\n",
    "X=np.random.rand(m,1)\n",
    "y = 4*(X-0.5)**2 #回归任务，标签是连续的。\n",
    "y = y + np.random.randn(m,1)/10 #设置随机抖动。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(max_depth=2)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor #决策树回归方法\n",
    "#见：https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html#sklearn.tree.DecisionTreeRegressor\n",
    "\n",
    "tree_reg = DecisionTreeRegressor(max_depth=2)\n",
    "tree_reg.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "export_graphviz(\n",
    "        tree_reg,\n",
    "        out_file=(\"regression_tree.dot\"),\n",
    "        feature_names=[\"x1\"],\n",
    "        rounded=True,\n",
    "        filled=True\n",
    "    )\n",
    "\n",
    "# 在命令提示符中键入：dot -Tpng regression_tree.dot -o regression_tree.png  即可把dot文件转化为png图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 54,
     "metadata": {
      "image/png": {
       "height": 400,
       "width": 400
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 你的第二个决策树长这样\n",
    "from IPython.display import Image\n",
    "Image(filename=\"regression_tree.png\",width=400,height=400,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对比树的深度对结果的影响"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 792x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "\n",
    "tree_reg1 = DecisionTreeRegressor(random_state=42, max_depth=2)#深度设置为2\n",
    "tree_reg2 = DecisionTreeRegressor(random_state=42, max_depth=3)#深度设置为3\n",
    "tree_reg1.fit(X, y)\n",
    "tree_reg2.fit(X, y)\n",
    "\n",
    "def plot_regression_predictions(tree_reg, X, y, axes=[0, 1, -0.2, 1], ylabel=\"$y$\"):\n",
    "    x1 = np.linspace(axes[0], axes[1], 500).reshape(-1, 1)\n",
    "    y_pred = tree_reg.predict(x1)\n",
    "    plt.axis(axes)\n",
    "    plt.xlabel(\"$x_1$\", fontsize=18)\n",
    "    if ylabel:\n",
    "        plt.ylabel(ylabel, fontsize=18, rotation=0)\n",
    "    plt.plot(X, y, \"b.\")\n",
    "    plt.plot(x1, y_pred, \"r.-\", linewidth=2, label=r\"$\\hat{y}$\")\n",
    "\n",
    "plt.figure(figsize=(11, 4))\n",
    "plt.subplot(121)\n",
    "\n",
    "plot_regression_predictions(tree_reg1, X, y)\n",
    "for split, style in ((0.1973, \"k-\"), (0.0917, \"k--\"), (0.7718, \"k--\")):\n",
    "    plt.plot([split, split], [-0.2, 1], style, linewidth=2)\n",
    "plt.text(0.21, 0.65, \"Depth=0\", fontsize=15)#展示特征的切分点\n",
    "plt.text(0.01, 0.2, \"Depth=1\", fontsize=13)\n",
    "plt.text(0.65, 0.8, \"Depth=1\", fontsize=13)\n",
    "plt.legend(loc=\"upper center\", fontsize=18)\n",
    "plt.title(\"max_depth=2\", fontsize=14)\n",
    "\n",
    "plt.subplot(122)\n",
    "\n",
    "plot_regression_predictions(tree_reg2, X, y, ylabel=None)\n",
    "for split, style in ((0.1973, \"k-\"), (0.0917, \"k--\"), (0.7718, \"k--\")):\n",
    "    plt.plot([split, split], [-0.2, 1], style, linewidth=2)\n",
    "for split in (0.0458, 0.1298, 0.2873, 0.9040):\n",
    "    plt.plot([split, split], [-0.2, 1], \"k:\", linewidth=1)\n",
    "plt.text(0.3, 0.5, \"Depth=2\", fontsize=13)\n",
    "plt.title(\"max_depth=3\", fontsize=14)\n",
    "\n",
    "plt.show()#可以看到树的深度越深，切的越细致。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 792x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tree_reg1 = DecisionTreeRegressor(random_state=42)\n",
    "tree_reg2 = DecisionTreeRegressor(random_state=42, min_samples_leaf=10)#叶子节点具有的最小样本数设为10\n",
    "tree_reg1.fit(X, y)\n",
    "tree_reg2.fit(X, y)\n",
    "\n",
    "x1 = np.linspace(0, 1, 500).reshape(-1, 1)\n",
    "y_pred1 = tree_reg1.predict(x1)\n",
    "y_pred2 = tree_reg2.predict(x1)\n",
    "\n",
    "plt.figure(figsize=(11, 4))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.plot(X, y, \"b.\")\n",
    "plt.plot(x1, y_pred1, \"r.-\", linewidth=2, label=r\"$\\hat{y}$\")\n",
    "plt.axis([0, 1, -0.2, 1.1])\n",
    "plt.xlabel(\"$x_1$\", fontsize=18)\n",
    "plt.ylabel(\"$y$\", fontsize=18, rotation=0)\n",
    "plt.legend(loc=\"upper center\", fontsize=18)\n",
    "plt.title(\"No restrictions\", fontsize=14)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(X, y, \"b.\")\n",
    "plt.plot(x1, y_pred2, \"r.-\", linewidth=2, label=r\"$\\hat{y}$\")\n",
    "plt.axis([0, 1, -0.2, 1.1])\n",
    "plt.xlabel(\"$x_1$\", fontsize=18)\n",
    "plt.title(\"min_samples_leaf={}\".format(tree_reg2.min_samples_leaf), fontsize=14)\n",
    "\n",
    "plt.show()#可以看到没有\"叶子节点具有的最小样本数设为10\"的左图，把决策树做的很复杂。有点过拟合的意思。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "思考题："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1决策树可以做回归问题吗？与做分类问题时的区别和联系是什么？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以；\n",
    "相同：1.都采用树状结构，树的分支代表测试结果，叶子节点代表最终的预测结果\n",
    "2.采用递归方法\n",
    "3.都用最大深度最小样本数之类的条件来作为停止条件\n",
    "\n",
    "不同：分类决策树的输出的类别标签，回归决策树的叶子结点输出的是实数；\n",
    "分类回归树的变量目标是离散类别标签，目标变量是连续数值；\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2在决策树中，什么是根节点，叶子节点，分支？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根节点是决策树的起始节点。它包含了整个数据集，并且是进行首次分裂的地方。\n",
    "叶子节点是决策树的末端节点，不再进行任何分裂。每个叶子节点对应一个分类标签或一个预测值\n",
    "分支是决策树中的边，连接节点与节点，代表一个特征的取值范围或条件。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3你能说明决策树在训练阶段的流程吗？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1、初始化\n",
    "2、选择最佳分裂特征和分裂点\n",
    "3、数据集分裂\n",
    "4、递归构建出子树\n",
    "5、设定停止条件\n",
    "6、生成叶子结点"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4什么是熵，什么是信息增益？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "熵是度量随机变量不确定性的一种方式。熵越高，数据集的不确定性越大；熵越低，数据集越纯净\n",
    "\n",
    "\n",
    "信息增益用于衡量某个特征对分类的不确定性减少的程度。信息增益越大，说明该特征对分类的贡献越大，越适合作为分裂点。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "5调节决策树时，可以说出DecisionTreeClassifier下的参数有哪些，含义是什么吗？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "criterion 衡量分裂质量\n",
    "splitter   选择分裂点\n",
    "max_depth 树的最大深度\n",
    "min_samples_split 再分裂所需的最小样本数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "6下述代码每一句话的含义是什么？\n",
    "\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "clf = DecisionTreeClassifier(random_state=0)\n",
    "iris = load_iris()\n",
    "cross_val_score(clf, iris.data, iris.target, cv=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_iris#####从数据集中导入load_iris函数\n",
    "from sklearn.model_selection import cross_val_score####评估模型的性能\n",
    "from sklearn.tree import DecisionTreeClassifier######创建一个决策树分类模型\n",
    "clf = DecisionTreeClassifier(random_state=0)####确保决策树的结果可重复\n",
    "iris = load_iris()####将返回的数据集赋值给iris\n",
    "cross_val_score(clf, iris.data, iris.target, cv=10)###将数据集分成十分，纠纷训练模型，一份测试模型，重复十遍"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "7下述代码每一句话的含义是什么？\n",
    "\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "iris = load_iris()\n",
    "X = iris.data[:,2:]\n",
    "y = iris.target\n",
    "tree_clf = DecisionTreeClassifier(max_depth=2)\n",
    "tree_clf.fit(X,y)\n",
    "tree_clf.predict_proba([[5,1.5]])\n",
    "tree_clf.predict([[5,1.5]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_iris####加载数据集\n",
    "from sklearn.tree import DecisionTreeClassifier####创建分类模型\n",
    "iris = load_iris()####将返回的数据集赋值给IRIS\n",
    "X = iris.data[:,2:]######在数据集特征矩阵中选择所有行和第二列赋值给变量X\n",
    "y = iris.target####将数据集目标标签赋值给y\n",
    "tree_clf = DecisionTreeClassifier(max_depth=2)#####限制决策树最大深度为2\n",
    "tree_clf.fit(X,y)####用fit 方法构建决策树模型\n",
    "tree_clf.predict_proba([[5,1.5]])######用练好的分类器预测特征为【5,1,5】类别的概率\n",
    "tree_clf.predict([[5,1.5]])######预测特征为【5,1,5】的类别"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "8下面这句话的含义是什么？\n",
    "\n",
    "tree_clf2 = DecisionTreeClassifier(min_samples_leaf=4,random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "设置叶子结点最小样本数为4，随机种子为42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "9能理解上面生成的分类树iris_tree2.png和回归树regression_tree.png中的所有信息吗？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "10给定一个矩阵X，用来表达数据。如果想对矩阵X进行旋转来完成算法的鲁棒性实验，请问如何对矩阵X进行旋转？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "1、创建矩阵 X\n",
    "2、定义了旋转角度为 45 度，\n",
    "3、计算逆时针旋转的旋转矩阵 R，\n",
    "4、矩阵相乘将矩阵 X 进行逆时针旋转，\n",
    "5、输出旋转后的矩阵 X'。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "11下述代码的含义是什么？\n",
    "\n",
    "from sklearn.tree import DecisionTreeRegressor \n",
    "tree_reg = DecisionTreeRegressor(max_depth=2)\n",
    "tree_reg.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor #####导入决策树回归模型的 DecisionTreeRegressor 类\n",
    "tree_reg = DecisionTreeRegressor(max_depth=2)######创建决策树回归模型，设置最大深度为2\n",
    "tree_reg.fit(X,y)#####拟合训练"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "12决策树算法有哪些？什么是gini系数？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1、 Id3\n",
    "2、C4.5\n",
    "3、CART\n",
    "4、CHAID\n",
    "5、随机森林\n",
    "6、GBDT\n",
    "\n",
    "\n",
    "Gini系数是用于衡量决策树节点的纯度或不纯度的指标。基尼系数越小，表示节点的纯度越高，数据越趋于同一类别；基尼系数越大，表示节点的不纯度越高，数据分布越不均匀"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13简述决策树为什么要剪枝？简述什么是预剪枝，什么是后剪枝？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "防止模型过拟合，提高模型泛化能力。\n",
    "预剪枝：在每个节点判断分裂前，先进行判断是否需要进行分裂，如果不满足预定义的条件，则停止分裂，将当前节点设为叶子节点。\n",
    "后剪枝：在决策树生长完成后，通过逐步删除一些节点，并测试删除后的模型在验证集上的性能，若性能有所提升则保留该剪枝操作。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14决策树下，一个节点的Gini系数一般会比它的父节点的小还是大？一般而言，还是总是这样？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "一般比父节点小\n",
    "决策树的生成过程是通过选择分裂后基尼系数最小的特征来进行的。基尼系数用于衡量节点的不纯度，而分裂后的节点通常会比父节点更纯，即基尼系数更小。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "15如果决策树过拟合，减小深度是否会缓解这个问题？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以，减小深度可以降低模型复杂度，减少过拟合风险，提高泛化能力"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "16以下是目标变量在训练集上的 8 个实际值 [0,0,0,1,1,1,1,1]，目标变量的熵是多少？\n",
    "A -(5/8 log(5/8) + 3/8 log(3/8))\n",
    "B 5/8 log(5/8) + 3/8 log(3/8)\n",
    "C 3/8 log(5/8) + 5/8 log(3/8)\n",
    "D 5/8 log(3/8) – 3/8 log(5/8)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "选择A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "17树的深度具有更高或更低的取值对于决策树算法一定更好吗？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "不一定，更深的树可以提高模型训练的准确度，但是容易过拟合，泛化能力较差，计算较为复杂；\n",
    "更浅的树泛化能力较好，过拟合发生的概率较小，但是模型训练能力差，准确度低。\n",
    "所以应该根据需求和数据集的情况而定"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "18使用决策树分类器，设定最大深度是5，训练样本的特征是X_train,训练样本的标签是Y_train,训练模型，并给出测试样本的特征X_test的预测和预测概率。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "tree_clf = DecisionTreeClassifier(max_depth=5)\n",
    "tree_clf.fit(X_train, y_train)\n",
    "\n",
    "y_pred = tree_clf.predict(X_test)\n",
    "y_pred_proba = tree_clf.predict_proba(X_test)\n",
    "\n",
    "print(\"标签:\", y_pred)\n",
    "print(\"概率:\", y_pred_proba)\n"
   ]
  }
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